The memory layer multi-agent AI runs on.

Your agents are not the problem. The missing memory layer is.

Most enterprise AI failures are memory failures. An agent that cannot remember what it learned in the last session. A pipeline where the research agent and the drafting agent work from different versions of the same facts. A multi-agent workflow where entity identity is resolved independently by each agent.

The solution is a shared private memory layer that every agent reads from and writes to — maintained with Entity Coherence, continuously updated, and deployed in your own environment.

One memory. Every agent. Coherent across every handoff.

Shared institutional memory — every agent via MCP, API, or SDK reads from the same private memory vault.

Agent-to-agent context — handoffs pass context through shared memory, not prompt concatenation.

Entity Coherence across agents — one coherent entity across the pipeline, resolved at ingest.

Write-back on every query — retrieval enriches shared memory at query time.